Opendde Tools#

Configuration File: remote_tools/opendde_tools.json Tool Type: Remote Tools Count: 1

This page contains all tools defined in the opendde_tools.json configuration file.

Available Tools#

opendde_fold (Type: RemoteTool)#

Predict an all-atom biomolecular structure with OpenDDE 1.1.1, Aureka’s open AlphaFold3-class mod…

opendde_fold tool specification

Tool Information:

  • Name: opendde_fold

  • Type: RemoteTool

  • Description: Predict an all-atom biomolecular structure with OpenDDE 1.1.1, Aureka’s open AlphaFold3-class model. The query is a list of chains, each with a molecule_type (protein, dna, rna, ligand or ion) and a sequence – SMILES or CCD_<id> for a ligand, the element symbol for an ion. One call folds one complex for one seed into up to 5 diffusion samples; returns per-sample confidence scores (rank on ranking_score) and timings, and the mmCIF text is opt-in. Folds single-sequence: no MSA search is performed.

Parameters:

  • chains (array) (required) The chains of one complex.

  • name (string) (optional) A label for this complex; it names the output files. Defaults to ‘complex’.

  • seed (integer) (optional) Random seed; the same seed reproduces the prediction. Default 101.

  • num_diffusion_samples (integer) (optional) Structures to sample (upstream’s default is 5, and 5 is this server’s ceiling: peak memory scales with it). Each is scored separately, so this is how to compare conformations; rank them on scores.

  • num_diffusion_steps (integer) (optional) Diffusion steps per sample (upstream’s default is 200). Fewer is faster and coarser.

  • num_recycles (integer) (optional) Pairformer recycling cycles (upstream’s default is 10). Fewer is faster and less accurate.

  • return_structures (boolean) (optional) Return the mmCIF text (default false: megabytes). The confidence scores come back either way.

Example Usage:

query = {
    "name": "opendde_fold",
    "arguments": {
        "chains": ["item1", "item2"]
    }
}
result = tu.run(query)